Effects of Lithium Carbonate and Superplasticizer on Ultra-Early Strength of Alite-Ye'elimite-Belite-Ferrite Cement.

Alite-ye'elimite-belite-ferrite cement (AYBFC) integrates the advantages of calcium sulfoaluminate cement and Portland cement, but its ultra-early strength needs to be further improved when applied to rush repair and construction works. In this study, the ultra-early strength of AYBFC was improved using lithium carbonate (Li2CO3) and superplasticizer. The results showed that an appropriate amount of Li2CO3 could significantly improve the ultra-early strength of AYBFC, since it was capable of promoting the hydration reaction of AYBFC. After polycarboxylate superplasticizer was doped on this basis, the ultra-early compressive strength of AYBFC was further improved. This was because the superplasticizer could markedly enhance the matrix compactness despite its inhibitory effect on the hydration reaction of cement and the generation of hydration products.

More attention should be paid to Omicron-associated sepsis: a multicenter retrospective study in south China.

Background: The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly transmissible but causes less severe disease compared to other variants. However, its association with sepsis incidence and outcomes is unclear. This study aimed to investigate the incidence of Omicron-associated sepsis, as per the Sepsis 3.0 definition, in hospitalized patients, and to explore its relationship with clinical characteristics and prognosis. Methods: This multicenter retrospective study included adults hospitalized with confirmed SARS-CoV-2 infection across six tertiary hospitals in Guangzhou, China from November 2022 to January 2023. The Sequential Organ Failure Assessment (SOFA) score and its components were calculated at hospital admission to identify sepsis. Outcomes assessed were need for intensive care unit (ICU) transfer and mortality. Receiver operating characteristic curves evaluated the predictive value of sepsis versus other biomarkers for outcomes. Results: A total of 299 patients (mean age: 70.1±14.4 years, 42.14% female) with SOFA score were enrolled. Among them, 152 were categorized as non-serious cases while the others were assigned as the serious group. The proportion of male patients, unvaccinated patients, patients with comorbidity such as diabetes, chronic cardiovascular disease, and chronic lung disease was significantly higher in the serious than non-serious group. The median SOFA score of all enrolled patients was 1 (interquartile range, 0-18). In our study, 147 patients (64.19%) were identified as having sepsis upon hospital admission, with the majority of these septic patients (113, representing 76.87%) being in the serious group, the respiratory, coagulation, cardiovascular, central nervous, and renal organ SOFA scores were all significantly higher in the serious compared to the non-serious group. Among septic patients, 20 out of 49 (40.81%) had septic shock as indicated by lactate measurement within 24 hours of admission, and the majority of septic patients were in the serious group (17/20, 76.87%). Sepsis was present in 118 out of 269 (43.9%) patients in the general ward, and among those with sepsis, 34 out of 118 (28.8%) later required ICU care during hospitalization. By contrast, none of the patients without sepsis required ICU care. Moreover, the mortality rate was significantly higher in patients with than without sepsis. Conclusions: A considerable proportion of patients infected with Omicron present with sepsis upon hospital admission, which is associated with a poorer prognosis. Therefore, early recognition of viral sepsis by evaluation of the SOFA score in hospitalized coronavirus disease 2019 patients is crucial.

Association between chronic obstructive pulmonary disease and 28-day mortality in patients with sepsis: a retrospective study based on the MIMIC-III database.

BACKGROUND: Sepsis is a common cause of mortality in critically ill patients, and chronic obstructive pulmonary disease (COPD) is one of the most common comorbidities in septic patients. However, the impact of COPD on patients with sepsis remained unclear. Therefore, the purpose of this study aimed to assess the effect of COPD on the prognosis of septic patients based on Medical Information Mart for Intensive Care (MIMIC-III) database. METHODS: In this retrospective study based on the (MIMIC)-III database version 1.4 (v1.4), we collected clinical data and 28-day all-cause mortality from patients with sepsis in intensive care unit (ICU) and these patients met the diagnostic criteria of Sepsis 3 on ICU admission between 2008 and 2012. International Classification of Diseases (ICD-9) (4660, 490, 4910, 4911, 49120, 49121, 4918, 4919, 4920, 4928, 494, 4940, 4941, 496) was used to identified COPD. We applied Kaplan-Meier analysis to compare difference of 28-day all-cause mortality between septic patients with and without COPD. Cox proportional-hazards model was applied to explore the risk factor associated with 28-day all-cause mortality in patients with sepsis. RESULTS: Six thousand two hundred fifty seven patients with sepsis were included in this study, including 955 (15.3%) patients with COPD and 5302 patients without COPD (84.7%). Compared with patients without COPD, patients with COPD were older (median: 73.5 [64.4, 82.0] vs 65.8 [52.9, 79.1], P < 0.001), had higher simplified acute physiology score II (SAPSII) (median: 40.0 [33.0, 49.0] vs 38.0 [29.0,47.0], P < 0.001) and greater proportion of mechanical ventilatory support (MV) (55.0% vs 48.9%, P = 0.001). In our study, septic patients with COPD had higher 28-day all-cause mortality (23.6% vs 16.4%, P < 0.001) than patients without COPD. After adjusting for covariates, the results showed that COPD was an independent risk factor for the 28-day all-cause mortality of patients with sepsis (HR 1.30, 95%CI: 1.12-1.50, P = 0.001). CONCLUSIONS: COPD was an independent risk factor of 28-day all-cause mortality in septic patients. Clinically, septic patients with COPD should be given additional care.

High driving pressure ventilation induces pulmonary hypertension in a rabbit model of acute lung injury.

BACKGROUND: Mechanical ventilation may cause pulmonary hypertension in patients with acute lung injury (ALI), but the underlying mechanism remains elucidated. METHODS: ALI was induced in rabbits by a two-hit injury, i.e., hydrochloric acid aspiration followed by mechanical ventilation for 1 h. Rabbits were then ventilated with driving pressure of 10, 15, 20, or 25 cmH2O for 7 h. Clinicopathological parameters were measured at baseline and different timepoints of ventilation. RNA sequencing was conducted to identify the differentially expressed genes in high driving pressure ventilated lung tissue. RESULTS: The two-hit injury induced ALI in rabbits was evidenced by dramatically decreased PaO2/FiO2 in the ALI group compared with that in the control group (144.5 ± 23.8 mmHg vs. 391.6 ± 26.6 mmHg, P < 0.001). High driving pressure ventilation (20 and 25 cmH2O) significantly elevated the parameters of acute pulmonary hypertension at different timepoints compared with low driving pressure (10 and 15 cmH2O), along with significant increases in lung wet/dry ratios, total protein contents in bronchoalveolar lavage fluid, and lung injury scores. The high driving pressure groups showed more pronounced histopathological abnormalities in the lung compared with the low driving pressure groups, accompanied by significant increases in the cross-sectional areas of myocytes, right ventricular weight/body weight value, and Fulton's index. Furthermore, the expression of the genes related to ferroptosis induction was generally upregulated in high driving pressure groups compared with those in low driving pressure groups. CONCLUSIONS: A rabbit model of ventilation-induced pulmonary hypertension in ALI was successfully established. Our results open a new research direction investigating the exact role of ferroptosis in ventilation-induced pulmonary hypertension in ALI.

A diagnostic model for sepsis-induced acute lung injury using a consensus machine learning approach and its therapeutic implications.

BACKGROUND: A significant proportion of septic patients with acute lung injury (ALI) are recognized late due to the absence of an efficient diagnostic test, leading to the postponed treatments and consequently higher mortality. Identifying diagnostic biomarkers may improve screening to identify septic patients at high risk of ALI earlier and provide the potential effective therapeutic drugs. Machine learning represents a powerful approach for making sense of complex gene expression data to find robust ALI diagnostic biomarkers. METHODS: The datasets were obtained from GEO and ArrayExpress databases. Following quality control and normalization, the datasets (GSE66890, GSE10474 and GSE32707) were merged as the training set, and four machine learning feature selection methods (Elastic net, SVM, random forest and XGBoost) were applied to construct the diagnostic model. The other datasets were considered as the validation sets. To further evaluate the performance and predictive value of diagnostic model, nomogram, Decision Curve Analysis (DCA) and Clinical Impact Curve (CIC) were constructed. Finally, the potential small molecular compounds interacting with selected features were explored from the CTD database. RESULTS: The results of GSEA showed that immune response and metabolism might play an important role in the pathogenesis of sepsis-induced ALI. Then, 52 genes were identified as putative biomarkers by consensus feature selection from all four methods. Among them, 5 genes (ARHGDIB, ALDH1A1, TACR3, TREM1 and PI3) were selected by all methods and used to predict ALI diagnosis with high accuracy. The external datasets (E-MTAB-5273 and E-MTAB-5274) demonstrated that the diagnostic model had great accuracy with AUC value of 0.725 and 0.833, respectively. In addition, the nomogram, DCA and CIC showed that the diagnostic model had great performance and predictive value. Finally, the small molecular compounds (Curcumin, Tretinoin, Acetaminophen, Estradiol and Dexamethasone) were screened as the potential therapeutic agents for sepsis-induced ALI. CONCLUSION: This consensus of multiple machine learning algorithms identified 5 genes that were able to distinguish ALI from septic patients. The diagnostic model could identify septic patients at high risk of ALI, and provide potential therapeutic targets for sepsis-induced ALI.

Inhalation of ACE2 as a therapeutic target on sex-bias differences in SARS-CoV-2 infection and variant of concern.

Despite similar infection rates, COVID-19 has resulted in more deaths in men than women. To understand the underlying mechanisms behind this sex-biased difference in disease severity, we infected K18-human angiotensin converting enzyme 2 (ACE2) mice of both sexes with SARS-CoV-2. Our study revealed a unique protein expression profile in the lung microenvironment of female mice. As a result, they were less vulnerable to severe infection, with higher ACE2 expression and a higher estrogen receptor α (ERα)/androgen receptor (AR) ratio that led to increased antiviral factor levels. In male mice, inhaling recombinant ACE2 neutralized the virus and maintained the ERα/AR ratio, thereby protecting the lungs. Our findings suggest that inhaling recombinant ACE2 could serve as a decoy receptor against SARS-CoV-2 and protect male mice by offsetting ERα-associated protective mechanisms. Additionally, our study supports the potential effectiveness of recombinant ACE2 therapy in human lung organoids infected with the Delta variant.

The accuracy of simplified calculation of mechanical power: a simulation study.

Background: Mechanical ventilation (MV) is an important life-saving method in the intensive care unit (ICU). A lower mechanical power (MP) is associated with a better MV strategy. However, traditional MP calculating methods are complicated, and algebraic formulas seem to be rather practical. The aim of the present study was to compare the accuracy and application of different algebraic formulas calculating MP. Methods: A lung simulator, TestChest, was used to simulate pulmonary compliance variations. Using the TestChest system software, the parameters, including compliance and airway resistance, were set to simulate various acute respiratory distress syndrome (ARDS) lungs. Ventilator was also set to volume- and pressure-controlled modes with various parameter values (respiratory rate, RR, time of inspiration, Tinsp, positive end-expiratory pressure, PEEP) to ventilate the simulated lung of ARDS (with various respiratory system compliance, Crs). For the lung simulator, resistance of airway (Raw) was fixed to 5 cmH2O/L/s. Crs below lower inflation point (LIP) or above upper inflation point (UIP) was set to 10 mL/cmH2O. The reference standard geometric method was calculated offline with a customized software. Three algebraic formulas for volume-controlled and three for pressure-controlled were used to calculate MP. Results: The performances of the formulas were different, although the derived MP were significantly correlated with that derived from the reference method (R2>0.80, P<0.001). Under volume-controlled ventilation, medians of MP calculated with one equation was significantly lower than that with the reference method (P<0.001). Under pressure-controlled ventilation, median of MP calculated with two equations were significantly higher (P<0.001). The maximum difference was over 70% of the MP value calculated with the reference method. Conclusions: The algebraic formulas may introduce considerably large bias under the presented lung conditions, especially in moderate to severe ARDS. Cautious is required when selecting adequate algebraic formulas to calculate MP based on the formula's premises, ventilation mode, and patients' status. In clinical practice, the trend rather than the value of MP calculated by formulas should require more attention.

Ferroptosis, pyroptosis and necroptosis in acute respiratory distress syndrome.

Acute respiratory distress syndrome (ARDS) is an acute and uncontrolled pulmonary inflammation caused by various insults. Cell death is a critical mechanism in the pathogenesis of ARDS. Ferroptosis, a novel form of cell death defined as iron-mediated lipid peroxidation, has been shown to play a role in the pathogenesis of ARDS. Additionally, pyroptosis and necroptosis are also involved in the pathophysiological process of ARDS. The crosstalk among ferroptosis, pyroptosis, and necroptosis is getting increasing attention. Therefore, this review will mainly summarize the molecular mechanisms and central pathophysiological role of ferroptosis in ARDS. We will also discuss our understanding of pyroptosis and necroptosis as they pertain to the pathogenesis of ARDS. Furthermore, we also describe the pathological processes that engage crosstalk among ferroptosis, pyroptosis, and necroptosis. We consider that individual pathways of ferroptosis, pyroptosis, and necroptosis are highly interconnected and can compensate for one another to promote cell death.

The Synergistic Effects of Ultrafine Slag Powder and Limestone on the Rheology Behavior, Microstructure, and Fractal Features of Ultra-High Performance Concrete (UHPC).

This study investigated the effect of the interaction between ultrafine slag powder (USL) and limestone (LS) on the rheology behavior, microstructure, and fractal features of UHPC. The results indicated that B2 with mass ratio of 2:1 between the USL and LS obtained the highest compressive strength and the lowest yield stress. The combination of the USL and LS facilitated the cement hydration, ettringite, and monocarboaluminate (Mc) formation, as well as the increase in the polymerization of the C-S-H. The synergistic action between the USL and LS refined the pore structure due to the formation of the Mc, compensating for the consumption of the CH by the pozzolanic reaction, which provided a denser microstructure in the UHPC. The fractal dimension (Ds) of the UHPC was strongly related to the concrete pore structures and the compressive strength, which demonstrated that a new metric called the Ds value may be used to assess the synergistic effect of the UHPC.

Corrigendum: Construction and validation of a robust prognostic model based on immune features in sepsis.

[This corrects the article DOI: 10.3389/fimmu.2022.994295.].

ATOH8 binds SMAD3 to induce cellular senescence and prevent Ras-driven malignant transformation.

The process of oncogene-induced senescence (OIS) and the conversion between OIS and malignant transformation during carcinogenesis is poorly understood. Here, we show that following overactivation of oncogene Ras in lung epithelial cells, high-level transforming growth factor ß1 (TGF-ß1)-activated SMAD3, but not SMAD2 or SMAD4, plays a determinant role in inducing cellular senescence independent of the p53/p16/p15 senescence pathways. Importantly, SMAD3 binds a potential tumor suppressor ATOH8 to form a transcriptional complex that directly represses a series of cell cycle-promoting genes and consequently causes senescence in lung epithelial cells. Interestingly, the prosenescent SMAD3 converts to being oncogenic and essentially facilitates oncogenic Ras-driven malignant transformation. Furthermore, depleting Atoh8 rapidly accelerates oncogenic Ras-driven lung tumorigenesis, and lung cancers driven by mutant Ras and Atoh8 loss, but not by mutant Ras only, are sensitive to treatment of a specific SMAD3 inhibitor. Moreover, hypermethylation of the ATOH8 gene can be found in approximately 12% of clinical lung cancer cases. Together, our findings demonstrate not only epithelial cellular senescence directed by a potential tumor suppressor-controlled transcriptional program but also an important interplay between the prosenescent and transforming effects of TGF-ß/SMAD3, potentially laying a foundation for developing early detection and anticancer strategies.

PKMYT1 inhibits lung adenocarcinoma progression by abrogating AKT1 activity.

PURPOSE: AKT hyperactivation drives malignant phenotypes in lung cancer via promoting tumor cell proliferation and survival. However, the relationship between dysregulation of cell cycle progression and AKT1 kinase activity is still not clear. METHODS: Following the expression level of PKMYT1 in lung cancer, we performed cell proliferation, migration, invasion, and xenograft assays to determine the function of PKMYT1. We used RNA-seq to explore the anti-tumor mechanism of PKMYT1 and examined the effect of PKMYT1 on AKT1 activity. RESULTS: In this study, we report that PKMYT1 is downregulated in lung adenocarcinoma (LUAD) tissues and its low expression predicts a poor prognosis in LUAD patients. PKMYT1 exerts potent tumor-suppressive functions in LUAD cells by inhibiting AKT1 activation and thereby repressing cell cycle progression, which depends on its tyrosine and threonine protein kinase activity. Interestingly, PKMYT1 could directly bind AKT1 to abrogate AKT1 activation. Moreover, silencing AKT1 and inhibitors targeting the AKT pathway effectively reverse the promoting effects of PKMYT1 knockdown on proliferation, migration and invasion of LUAD cells. CONCLUSION: This work reveals the anti-tumor effect of PKMYT1 in LUAD and provides evidence to clarify the dual roles of PKMYT1 in tumor progression. Moreover, our findings broaden the current understandings on AKT1 activation and identify PKMYT1 as a potential negative regulator of AKT1 kinase activity, providing further insights into targeting the AKT pathway in LUAD.

Construction and validation of a robust prognostic model based on immune features in sepsis.

Purpose: Sepsis, with life-threatening organ failure, is caused by the uncontrolled host response to infection. Immune response plays an important role in the pathophysiology of sepsis. Immune-related genes (IRGs) are promising novel biomarkers that have been used to construct the diagnostic and prognostic model. However, an IRG prognostic model used to predict the 28-day mortality in sepsis was still limited. Therefore, the study aimed to develop a prognostic model based on IRGs to identify patients with high risk and predict the 28-day mortality in sepsis. Then, we further explore the circulating immune cell and immunosuppression state in sepsis. Materials and methods: The differentially expressed genes (DEGs), differentially expressed immune-related genes (DEIRGs), and differentially expressed transcription factors (DETFs) were obtained from the GEO, ImmPort, and Cistrome databases. Then, the TFs-DEIRGs regulatory network and prognostic prediction model were constructed by Cox regression analysis and Pearson correlation analysis. The external datasets also validated the reliability of the prognostic model. Based on the prognostic DEIRGs, we developed a nomogram and conducted an independent prognosis analysis to explore the relationship between DEIRGs in the prognostic model and clinical features in sepsis. Besides, we further evaluate the circulating immune cells state in sepsis. Results: A total of seven datasets were included in our study. Among them, GSE65682 was identified as a discovery cohort. The results of GSEA showed that there is a significant correlation between sepsis and immune response. Then, based on a P value <0.01, 69 prognostic DEIRGs were obtained and the potential molecular mechanisms of DEIRGs were also clarified. According to multivariate Cox regression analysis, 22 DEIRGs were further identified to construct the prognostic model and identify patients with high risk. The Kaplan-Meier survival analysis showed that high-risk groups have higher 28-day mortality than low-risk groups (P=1.105e-13). The AUC value was 0.879 which symbolized that the prognostic model had a better accuracy to predict the 28-day mortality. The external datasets also prove that the prognostic model had an excellent prediction value. Furthermore, the results of correlation analysis showed that patients with Mars1 might have higher risk scores than Mars2-4 (P=0.002). According to the previous study, Mars1 endotype was characterized by immunoparalysis. Thus, the sepsis patients in high-risk groups might exist the immunosuppression. Between the high-risk and low-risk groups, circulating immune cells types were significantly different, and risk score was significantly negatively correlated with naive CD4+ T cells (P=0.019), activated NK cells (P=0.0045), monocytes (P=0.0134), and M1 macrophages (P=0.0002). Conclusions: Our study provides a robust prognostic model based on 22 DEIRGs which can predict 28-day mortality and immunosuppression status in sepsis. The higher risk score was positively associated with 28-day mortality and the development of immunosuppression. IRGs are a promising biomarker that might facilitate personalized treatments for sepsis.

Electrical impedance tomography for titration of positive end-expiratory pressure in acute respiratory distress syndrome patients with chronic obstructive pulmonary disease.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is one of most common comorbidities in acute respiratory distress syndrome (ARDS). There are few specific studies on the appropriate ventilation strategy for patients with ARDS comorbid with COPD, especially regarding on positive end-expiratory pressure (PEEP) titration. METHODS: To compare the respiratory mechanics in mechanical ventilated ARDS patients with or without COPD and to determine whether titration of PEEP based on electrical impedance tomography (EIT) is superior to the ARDSnet protocol. This is a single center, perspective, repeated measure study. ARDS patients requiring mechanical ventilation who were admitted to the intensive care unit between August 2017 and December 2020 were included. ARDS patients were divided according to whether they had COPD into a COPD group and a non-COPD group. Respiratory mechanics, gas exchange, and hemodynamics during ventilation were compared between the groups according to whether the PEEP level was titrated by EIT or the ARDSnet protocol. RESULTS: A total of twenty-seven ARDS patients including 14 comorbid with and 13 without COPD who met the study eligibility criteria were recruited. The PEEP levels titrated by EIT and the ARDSnet protocol were lower in the COPD group than in the non-COPD group (6.93 ± 1.69 cm H2O vs. 12.15 ± 2.40 cm H2O, P < 0.001 and 10.43 ± 1.20 cm H2O vs. 14.0 ± 3.0 cm H2O, P < 0.001, respectively). In the COPD group, the PEEP level titrated by EIT was lower than that titrated by the ARDSnet protocol (6.93 ± 1.69 cm H2O vs. 10.43 ± 1.20 cm H2O, P < 0.001), as was the global inhomogeneity (GI) index (0.397 ± 0.040 vs. 0.446 ± 0.052, P = 0.001), plateau airway pressure (16.50 ± 4.35 cm H2O vs. 20.93 ± 5.37 cm H2O, P = 0.001), dead space ventilation ratio (48.29 ± 6.78% vs. 55.14 ± 8.85%, P < 0.001), ventilation ratio (1.63 ± 0.33 vs. 1.87 ± 0.33, P < 0.001), and mechanical power (13.92 ± 2.18 J/min vs. 15.87 ± 2.53 J/min, P < 0.001). The cardiac index was higher when PEEP was treated by EIT than when it was titrated by the ARDSnet protocol (3.41 ± 0.50 L/min/m2 vs. 3.02 ± 0.43 L/min/m2, P < 0.001), as was oxygen delivery (466.40 ± 71.08 mL/min/m2 vs. 411.10 ± 69.71 mL/min/m2, P = 0.001). CONCLUSION: Titrated PEEP levels were lower in patients with ARDS with COPD than in ARDS patients without COPD. In ARDS patient comorbid with COPD, application of PEEP titrated by EIT was lower than those titrated by the ARDSnet protocol, which contributed to improvements in the ventilation ratio, mechanical energy, cardiac index, and oxygen delivery with less of an adverse impact on hemodynamics.

Association between active cytomegalovirus infection and lung fibroproliferation in adult patients with acute respiratory distress syndrome: a retrospective study.

BACKGROUND: Cytomegalovirus (CMV) has high seroprevalence, and its active infection is associated with several adverse prognoses in adult patients with acute respiratory distress syndrome (ARDS). However, the role of active CMV infection in ARDS-associated fibroproliferation is unknown. This study aimed at determining the association between active CMV infection and lung fibroproliferation in adult patients with ARDS. METHODS: We retrospectively reviewed the medical records of all adult patients with ARDS who were admitted to the intensive care unit (ICU) from January 2018 to December 2020 at a national university-affiliated hospital in China. Study subjects were divided into active and non-active CMV infection groups based on CMV DNAemia within a 28-day ICU hospitalization. Lung fibroproliferation was measured using chest high-resolution computed tomography (HRCT) and N-terminal peptide of serum procollagen III (NT-PCP-III) within the first 28 days of ICU admission. Pulmonary fibrosis, clinical features, laboratory findings, treatment measures, and clinical outcomes were compared between the two groups. RESULTS: Among the 87 ARDS patients included in this study, the incidence of active CMV infection was 16.1% within the 28-day ICU admission period. In logistic regression analyze, active CMV infection was found to be associated with higher pulmonary fibrogenesis, pulmonary fibrosis score, and NT-PCP-III level (P < 0.05). The duration of ICU stay in ARDS patients with active CMV infection was significantly higher than in those without active CMV infection (P < 0.05). CONCLUSIONS: Among adult patients with ARDS, active CMV infection was related to poor clinical outcomes. Active CMV infection was associated with ARDS-associated fibroproliferation. Prophylactic and preemptive use of anti-CMV agents on pulmonary fibrosis should be assessed to determine a consensus therapeutic strategy.

A Pan-Cancer Analysis of the Oncogenic Role of BCL7B: A Potential Biomarker for Prognosis and Immunotherapy.

Background: Previous studies have partly explored the role of B-cell CLL/lymphoma 7 protein family member B (BCL7B) in tumorigenesis and development. However, the prognosis and immunoregulatory value of BCL7B in pan-cancer patients remains unclear. Methods: Through The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases, the distinct expression of BCL7B gene in 33 tumors and adjacent normal tissues was analyzed. The Kaplan-Meier method (univariate Cox regression analysis and Kaplan-Meier curve) was used to identify the cancer types whose BCL7B gene expression was related to prognosis. The receiver operating characteristic (ROC) curve was used to elucidate the diagnosis value of BCL7B gene. Spearman's rank correlation coefficient was used to explore the relationship between BCL7B gene expression and immune cell infiltration, immune checkpoints, DNA methylation, DNA repair genes, immune-activating genes, immune-suppressing genes, immune subtypes, tumor mutation burden (TMB), and microsatellite instability (MSI). The Wilcoxon rank sum test and Kruskal-Wallis test were used to compare the expression of BCL7B gene in tumor tissues with different clinicopathological features. Gene set enrichment analysis (GSEA) was conducted to identify the tumor-related pathways in pan-cancer. The Human Protein Atlas (HPA) database was used to verify the BCL7B gene expression at the protein level. Results: High expression of BCL7B was associated with an inferior prognosis in glioblastoma multiforme (GBM), glioma (GBMLGG), kidney chromophobe (KICH), brain lower grade glioma (LGG), oral squamous cell carcinoma (OSCC), rectum adenocarcinoma (READ), and uveal melanoma (UVM). Low expression of BCL7B was associated with a poor prognosis in kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), skin cutaneous melanoma (SKCM), thyroid carcinoma (THCA), and sarcoma (SARC). The BCL7B gene expression had varying degrees of correlation with 24 immune cell subsets in 37 tumor environments such as adrenocortical carcinoma (ACC) and bladder urothelial carcinoma (BCLA). Spearman's rank correlation coefficient showed that BCL7B gene expression had different degrees of correlation with 47 immune checkpoints, 46 immune-activating genes, 24 immune-suppressing genes, 5 DNA repair genes, and DNA methylation, TMB, and MSI in 39 tumors. GSEA suggested that BCL7B was notably associated with cancer-related and immune-related pathways. Conclusion: In summary, BCL7B gene has a high diagnostic and prognostic value in pan-cancer and is related to the infiltration of 24 immune cell subsets in pan-cancer.

Development and validation of a clinical risk model to predict the hospital mortality in ventilated patients with acute respiratory distress syndrome: a population-based study.

BACKGROUND: Large variability in mortality exists in patients of acute respiratory distress syndrome (ARDS), especially those with invasive ventilation. The aim of this study was to develop a model to predict risk of in-hospital death in ventilated ARDS patients. METHODS: Ventilated patients with ARDS from two public databases (MIMIC-III and eICU-CRD) were randomly divided as training cohort and internal validation cohort. Least absolute shrinkage and selection operator (LASSO) and then Logistic regression was used to construct a predictive model with demographic, clinical, laboratory, comorbidities and ventilation variables ascertained at first 24 h of ICU admission and invasive ventilation. Our model was externally validated using data from another database (MIMIC-IV). RESULTS: A total of 1075 adult patients from MIMIC-III and eICU were randomly divided into training cohort (70%, n = 752) and internal validation cohort (30%, n = 323). 521 patients were included from MIMIC-IV. From 176 potential predictors, 9 independent predictive factors were included in the final model. Five variables were ascertained within the first 24 h of ICU admission, including age (OR, 1.02; 95% CI: 1.01-1.03), mean of respiratory rate (OR, 1.04; 95% CI: 1.01-1.08), the maximum of INR (OR, 1.14; 95% CI: 1.03-1.31) and alveolo-arterial oxygen difference (OR, 1.002; 95% CI: 1.001-1.003) and the minimum of RDW (OR, 1.17; 95% CI: 1.09-1.27). And four variables were collected within the first 24 h of invasive ventilation: mean of temperature (OR, 0.70; 95% CI: 0.57-0.86), the maximum of lactate (OR, 1.15; 95% CI: 1.09-1.22), the minimum of blood urea nitrogen (OR, 1.02; 95% CI: 1.01-1.03) and white blood cell counts (OR, 1.03; 95% CI: 1.01-1.06). Our model achieved good discrimination (AUC: 0.77, 95% CI: 0.73-0.80) in training cohort but the performance declined in internal (AUC: 0.75, 95% CI: 0.69-0.80) and external validation cohort (0.70, 95% CI: 0.65-0.74) and showed modest calibration. CONCLUSIONS: A risk score based on routinely collected variables at the start of admission to ICU and invasive ventilation can predict mortality of ventilated ARDS patients, with a moderate performance.

Weaning critically ill patients from mechanical ventilation: a protocol from a multicenter retrospective cohort study.

BACKGROUND: Mechanical ventilation (MV) is an important lifesaving method in intensive care unit (ICU). Prolonged MV is associated with ventilator associated pneumonia (VAP) and other complications. However, premature weaning from MV may lead to higher risk of reintubation or mortality. Therefore, timely and safe weaning from MV is important. In addition, identification of the right patient and performing a suitable weaning process is necessary. Although several guidelines about weaning have been reported, compliance with these guidelines is unknown. Therefore, the aim of this study is to explore the variation of weaning in China, associations between initial MV reason and clinical outcomes, and factors associated with weaning strategies using a multicenter cohort. METHODS: This multicenter retrospective cohort study will be conducted at 17 adult ICUs in China, that included patients who were admitted in this 17 ICUs between October 2020 and February 2021. Patients under 18 years of age and patients without the possibility for weaning will be excluded. The questionnaire information will be registered by a specific clinician in each center who has been evaluated and qualified to carry out the study. DISCUSSION: In a previous observational study of weaning in 17 ICUs in China, weaning practices varies nationally. Therefore, a multicenter retrospective cohort study is necessary to be conducted to explore the present weaning methods used in China. TRIAL REGISTRATION: Chinese Clinical Trial Registry (ChiCTR) (No. ChiCTR2100044634).

[Effect of oxidative stress response in acute respiratory distress syndrome caused by influenza].

Influenza virus is one of the common pathogens causing acute respiratory infectious diseases, and is easy to cause acute respiratory distress syndrome (ARDS) after infecting human body, which is an important cause of death of influenza patients. Influenza-induced ARDS results from a combination of overwhelming inflammation and immune response, causing tissue damage and apoptosis. Furthermore, virus-mediated oxidative stress is another important mechanism. Viral infection can produce excessive reactive oxygen species, which damage the epithelial-endothelial barrier with pulmonary edema. In this content, numerous studies have highlighted the importance of antioxidants as a new therapy aimed at blocking both viral replication and virus-induced inflammation. Therefore, this paper summarizes the epidemiology and mechanisms of influenza-induced ARDS, the role of oxidative stress in the occurrence and development of influenza-related ARDS and the role of antioxidants in anti influenza virus infection, in order to provide reference for effective treatment of influenza patients, reducing mortality, developing new anti influenza drugs and preventing and controlling influenza epidemic.